Remove Data Schemas Remove Data Warehouse Remove Engineering Remove Structured Data
article thumbnail

Implementing Data Contracts in the Data Warehouse

Monte Carlo

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

article thumbnail

Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

Netflix Tech

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Hands-On Introduction to Delta Lake with (py)Spark

Towards Data Science

Before going into further details on Delta Lake, we need to remember the concept of Data Lake, so let’s travel through some history. The main player in the context of the first data lakes was Hadoop, a distributed file system, with MapReduce, a processing paradigm built over the idea of minimal data movement and high parallelism.

article thumbnail

The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

article thumbnail

The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

article thumbnail

The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

article thumbnail

Top Data Catalog Tools

Monte Carlo

Table of Contents Alation Data Catalog Alteryx Connect Ataccama Atlan Castor Coginiti Collibra data.world erwin Data Catalog Informatica Enterprise Data Catalog (EDC) Metaphor Secoda Select Star Stemma Talend Data Catalog Zeenea A data catalog is only as good as the data it catalogs Alation Data Catalog Alation data catalog.